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Development case · blind model judgment pending independent human review; not a formal Benchmark conclusion.
AutocompleteNo-Evidence version preferred2 / 162 · e6bfbd7a9561cfcb

Bridging from single to collective cell migration: A review of models and links to experiments

Quantitative biology · 2011.10873v1

FLOWING EVIDENCE BENCHMARK

How do we tell whether Evidence helps?

At the same writing position, with the same model and task, how does supplying retrieved paper passages change the first output? We compare matched versions and retain ties, unusable outputs and incomplete reviews.

SAME DRAFT · EVIDENCE ON OR OFF

01 · FIXED WRITING POSITION

MANUSCRIPT

Same writing position ▌

Matched autocomplete at the same draft position

02 · TWO MATCHED INPUTS

SHARED BY BOTH

Manuscript context, model, task and prompt

A · With Evidence

Retrieved paper passages supplied

B · Without Evidence

No retrieved passages supplied

LLM

Same model and version

A → first output

B → first output

Blind judge agent

First outputs are anonymized as X and Y

Continuation review: accuracy, fit to the writing task and usability
Returns: X preferred / tie / Y preferred / both unusable

Order check: X / Y → Y / X

HOW DOES BLIND JUDGING WORK?

① Anonymize both outputs
The judge sees the same draft and both first outputs without knowing which received Evidence.

② Compare and swap order
The judge applies task-specific criteria in X/Y and then Y/X order.

③ Review disagreements
A third pass resolves disagreements. Incomplete reviews remain in the denominator.

How are autocomplete positions stratified?

Before seeing generation outcomes, we check whether a retrieved passage contains a specific proposition that directly supports the next writing move. Those positions appear in the left opportunity group; the rest are ordinary positions on the right. We select a balanced sample from admitted papers in each field. The 50/50 split is experimental, not a measure of how often either type occurs in writing.

AUTOCOMPLETE · 110

Biology, statistics and astrophysics

55 positions on each side; statistics uses the ten-paper rerun.

AUTOCOMPLETE · 52

Psychology and climate science

26 positions on each side; psychology includes nine papers and climate science four.

How are the table percentages calculated?

Across five fields, 51 of 81 left-column positions preferred the Evidence version. Ties, pairs where both versions were unusable and incomplete reviews remain in the denominator.

51Evidence version preferred
÷
81All positions in this group
=
63%Evidence preference in this group

Source contribution is a separate review: 16 of 22 Evidence wins entered into source review directly used retrieved papers; another 29 wins await review.

These are development-stage model judgments pending independent human review. They are not formal Benchmark conclusions and do not, on their own, establish causality.

Manuscript writing position

Text excerpt · not a PDF page

Research manuscript · excerpt

Bridging from single to collective cell migration: A review of models and links to experiments

5 Discussion

Overall, more experimental papers that probe the circuits that get recruited in the collective cell migration are needed. The papers [ 129 , 173 ] on the Merlin-Rac loop and on the link to YAP and E-cadherin [ 173 ] should be followed up with more detailed computational modeling and future rounds of experiments.

…l targets, and Fig 4 summarizes the ranges of relevance of both computational and experimental methods. Our review has focused on the topic of single and collective cell migration and its regulation. Likely motivated by development of disease therapies and NIH funding, or drug targets and support from pharmaceutical companies, the more medically oriented subjects such as cancer, liver toxicity, or lung morphogenesis, have fostered many generations of computational models. By comparison, the level of basic scientific computational research on multiscale cell biology modeling is still emerging.

↓ Next paragraph was generated here

The highlighted text is near the writing position. This is a layout of the evaluation input, not a PDF screenshot.

A matched comparison at the same writing positionJudgment: No-Evidence version preferred

Both arms use the same model, task and manuscript context. Only the retrieved passages differ. The first recorded output from each arm is shown below.

Evidence

Same model and position · retrieved passages supplied · first output

Not preferred in this comparison

The models reviewed here span a wide range of spatial and temporal scales, from stochastic descriptions of individual cell motion to continuum and agent-based treatments of collective migration. Bridging these scales remains a central challenge, since the parameters that govern single-cell behavior are not always the ones that determine tissue-level patterns.

Passages supplied to the Evidence version

100 years after Smoluchowski: stochastic processes in cell biology

We reviewed here the influential Smoluchowski equation and its applications in modeling, analysis in biophysics and computational cell biology.

No Evidence

Same model and position · no retrieved passages · first output

Preferred by blind review

This imbalance suggests that the choice of biological application, rather than the intrinsic multiscale character of the migration problem, has largely driven the development of computational models in this field. A more balanced research portfolio would couple the medically motivated models to equally detailed basic-science studies of the underlying migratory machinery.

Blind model judgment

The blinded model review preferred the no-Evidence version. Its original rationale appears below.

Read the original model judgment

Output A is fully grounded in the draft. It continues the contrast between medically-oriented computational research (cancer, liver toxicity, lung morphogenesis) and basic scientific computational research on multiscale cell biology, noting this imbalance and suggesting a more balanced approach. Every element traces to the draft's explicit claims about funding motivations and the emerging state of basic scientific computational research. Output B introduces unsupported claims: (1) 'stochastic descriptions of individual cell motion' - the source mentions 'stochastic processes' and the Smoluchowski equation but not individual cell motion in migration; (2) 'continuum and agent-based treatments of collective migration' - not mentioned in draft or source; (3) 'parameters that govern single-cell behavior are not always the ones that determine tissue-level patterns' - a substantive mechanistic claim about parameter relationships across scales with no support in the provided materials; (4) 'Bridging these scales remains a central challenge' - evaluative claim not grounded in the draft. The draft mentions 'multiscale cell biology modeling' as an emerging field but does not describe what scales are bridged, what methods are used, or what challenges exist. Output B reads as generic computational biology commentary rather than continuation of this specific manuscript's argument about funding imbalances.

The passages are input material; their presence does not mean an output used them or that they support every claim. Draft and source passages are excerpted; no simulated scores or PDF appear here.